PubMed · 4590526
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G W Evans, R B Howard. 1973. Personal space.. https://doi.org/10.1037/h0034946
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To determine if specific levels of vaccine cost and effectiveness exist that would support eventual respiratory syncytial virus (RSV) vaccine use in the elderly, a cost-effectiveness study was conducted comparing yearly administration of a hypothetical RSV vaccine among the 65-year-old US cohort to medical management of disease. Using base case assumptions - including a vaccine effectiveness against RSV-related hospitalization and death of 80% and a vaccine cost of US$33 - vaccine would result in 0.7 additional days of healthy life at a cost of US$9.82 per person. The cost per quality-adjusted life-year gained equaled US$5342 and remained reasonable over a wide range of vaccine cost and effectiveness. RSV vaccine would be cost-effective for the elderly population, with cost-effectiveness ratios similar to those for influenza vaccine.
Prognostic models can be developed with multiple regression analysis of a data set containing individual patient data. Often this data set is relatively small, while previously published studies present results for larger numbers of patients. We describe a method to combine univariable regression results from the medical literature with univariable and multivariable results from the data set containing individual patient data. This 'adaptation method' exploits the generally strong correlation between univariable and multivariable regression coefficients. The method is illustrated with several logistic regression models to predict 30-day mortality in patients with acute myocardial infarction. The regression coefficients showed considerably less variability when estimated with the adaptation method, compared to standard maximum likelihood estimates. Also, model performance, as distinguished in calibration and discrimination, improved clearly when compared to models including shrunk or penalized estimates. We conclude that prognostic models may benefit substantially from explicit incorporation of literature data.
Matching in case-control studies is a situation in which one wishes to make inferences about a parameter of interest in the presence of nuisance parameters. The usual approach is to apply a conditional likelihood. A bivariate latent class log-linear model for binomial responses is shown to yield a standard likelihood identical to the usual conditional one. This extension of the Rasch model for binary responses gives consistent estimates and a suitable likelihood function for cases matched with any fixed number of controls.